Neighborhood Rough Residual Network–Based Outlier Detection Method in IoT-Enabled Maritime Transportation Systems-Reference-Cited by-同舟云学术

Neighborhood Rough Residual Network–Based Outlier Detection Method in IoT-Enabled Maritime Transportation Systems

Published:2023-11 Issue:11 Volume:24 Page:11800-11811
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Chen Qiong¹^ORCID,Xie Liangru²,Zeng Lirong³^ORCID,Jiang Sining⁴^ORCID,Ding Weiping⁵^ORCID,Huang Xiaomeng¹^ORCID,Wang Hao⁶^ORCID

Affiliation:

1. Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China

2. Kingsoft Office Software, Jinshan Software Park, Zhuhai, China

3. State Key Laboratory of Marine Resource Utilization in South China Sea and the School of Information and Communication Engineering, Hainan University, Haikou, China

4. Department of Information Science and Engineering, Ocean University of China, Qingdao, China

5. School of Information Science and Technology, Nantong University, Nantong, China

6. Department of Computer Science, Norwegian University of Science and Technology, Gjøvik, Norway

Funder

National Key Research and Development Program of China

Open Foundation of Key Laboratory of Marine Science and Numerical Modeling

National Natural Science Foundation of China

Natural Science Key Foundation of Jiangsu Education Department

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10304348/10161585.pdf?arnumber=10161585

Reference60 articles.

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4. Deep learning for time series classification: a review

5. Data-Driven Trajectory Quality Improvement for Promoting Intelligent Vessel Traffic Services in 6G-Enabled Maritime IoT Systems

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